ACI open最新文献

{"title":"Development and Deployment of an Intraoperative Clinical Summary Document: A Veterans Health Care Affairs Perspective","authors":"Seshadri C. Mudumbai, T. Tanaka, E. Mariano","doi":"10.1055/s-0040-1701192","DOIUrl":"https://doi.org/10.1055/s-0040-1701192","url":null,"abstract":"Abstract Background Clinical summary documents that abstract details of episodes of care are essential to Advancing Care Information requirements for electronic health records. Few examples exist for intraoperative clinical summary documents (ICSD). Methods We describe the development and deployment of an ICSD at a tertiary hospital within the United States. Development included identification of needs of key stakeholders, evaluation of current clinical and data workflows, iterative development of prototypes with primary stakeholders, i.e., anesthesiologists and evaluation of prototypes with test patients. We deployed the ICSD over 6-months with tracking of (1) usage (number and types of end users and surgery types) and (2) written and oral feedback. Results Current workflows involved accessing a 10 to 40 page document presenting all surgery details with review described as burdensome. The ICSD prototype was a separate one-page summary optimized for viewing on a monitor or paper. The document had four sections: (1) administrative data, allergies, and precautions; (2) medications, infusions, and fluid intake and output; (3) airway assessments and a graphical presentation of hemodynamic trends (blood pressure), and (4) standardized text for events (hypotension) occurring intraoperatively. During the 6-month deployment, postanesthesia care unit and intensive care unit nurses were most prominent users followed by anesthesiologists. While overall well received, our pilot users reported challenges for readability, font size, and the lack of customization. Conclusion While the ICSD was designed for anesthesiologists, postanesthesia care unit and intensive care unit nurses were the most frequent users. Future development will involve customization for different stakeholders.","PeriodicalId":72041,"journal":{"name":"ACI open","volume":"04 1","pages":"e30 - e34"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1055/s-0040-1701192","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49573824","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Data Migration: A Thorny Issue in Electronic Health Record Transitions—Case Studies and Review of the Literature","authors":"R. Schreiber, Lawrence D Garber","doi":"10.1055/s-0040-1710007","DOIUrl":"https://doi.org/10.1055/s-0040-1710007","url":null,"abstract":"Abstract Objective To review the existing literature regarding data migration during electronic health record (EHR)-to-EHR transitions and add two case studies on this topic. Methods Very few publications exist that detail the processes and potential pitfalls of data migration during EHR transitions. One of the authors participated in a panel discussion at the American Medical Informatics Association symposium in 2015; at the time, only five empiric or experiential research articles on any aspect of EHR transitions were available. Of those, only two mentioned their experiences with data migration or conversions. A detailed PubMed and CINAHL (Cumulative Index to Nursing and Allied Health Literature) search in March 2019 yielded only one more article giving details about data migration. Results The two new case studies contrast starkly: one relied on manual abstraction and data entry, whereas the other leveraged several electronic tools. The literature reflects this diversity of approach: no two sites have reported the same approaches. The authors identify nine domains of potential consequences of the currently available techniques and offer mitigating strategies. Discussion Very little empiric information exists in the peer-reviewed literature regarding data migrations during EHR-to-EHR transitions; yet the case studies reflect that much remains suitable for a prospective study. Conclusion This report adds two new case studies to the six already reported in the literature. There is a wide disparity in techniques of data migration, each with its own set of pros and cons, which sites must consider during an EHR-to-EHR transition. Such transitions would benefit from prospective research on evaluation and knowledge discovery.","PeriodicalId":72041,"journal":{"name":"ACI open","volume":"04 1","pages":"e48 - e58"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1055/s-0040-1710007","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43260904","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Physician Burnout and Timing of Electronic Health Record Use.","authors":"Mark A Micek,&nbsp;Brian Arndt,&nbsp;Wen-Jan Tuan,&nbsp;Betsy Trowbridge,&nbsp;Shannon M Dean,&nbsp;Jennifer Lochner,&nbsp;Emmanuel Sampene,&nbsp;Nancy Pandhi","doi":"10.1055/s-0039-3401815","DOIUrl":"10.1055/s-0039-3401815","url":null,"abstract":"<p><strong>Background: </strong>Rates of burnout among physicians have been high in recent years. The Electronic Health Record (EHR) is implicated as a major cause of burnout.</p><p><strong>Objective: </strong>To determine the association between physician burnout and timing of EHR use in an academic internal medicine primary care practice.</p><p><strong>Methods: </strong>We conducted an observational cohort study using cross-sectional and retrospective data. Participants included primary care physicians in an academic outpatient general internal medicine practice. Burnout was measured with a single-item question via self-reported survey. EHR time was measured using retrospective automated data routinely captured within the institution's EHR. EHR time was separated into four categories: weekday workhours in-clinic time, weekday workhours out-of-clinic time, weekday afterhours time, and weekend/holiday afterhours time. Ordinal regression was used to determine the relationship between burnout and EHR time categories.</p><p><strong>Results: </strong>EHR use during in-clinic sessions was related to burnout in both bivariate (OR=1.04, 95% CI 1.01, 1.06; p=0.007) and adjusted (OR=1.07, 95% CI 1.03, 1.1; p=0.001) analyses. No significant relationships were found between burnout and afterhours EHR use.</p><p><strong>Conclusions: </strong>In this small single-institution study, physician burnout was associated with higher levels of in-clinic EHR use but not afterhours EHR use. Improved understanding of the variability of in-clinic EHR use, and the EHR tasks that are particularly burdensome to physicians, could help lead to interventions that better integrate EHR demands with clinical care and potentially reduce burnout. Further studies including more participants from diverse clinical settings are needed to further understand the relationship between burnout and afterhours EHR use.</p>","PeriodicalId":72041,"journal":{"name":"ACI open","volume":"4 1","pages":"e1-e8"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1055/s-0039-3401815","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41124216","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Using Electronic Health Record Data to Support Research and Quality Improvement: Practical Guidance from a Qualitative Investigation","authors":"R. Wasserman, Daria F. Ferro","doi":"10.1055/s-0040-1713421","DOIUrl":"https://doi.org/10.1055/s-0040-1713421","url":null,"abstract":"Abstract Objective The aim of the study is to identify how academic health centers (AHCs) have established infrastructures to leverage electronic health record (EHR) data to support research and quality improvement (QI). Methods Phone interviews of 18 clinical informaticians with expertise gained over three decades at 24 AHCs were transcribed for qualitative analysis on three levels. In Level I, investigators independently used NVivo software to code and identify themes expressed in the transcripts. In Level II, investigators reexamined coded transcripts and notes and contextualized themes in the learning health system paradigm. In Level III, an informant subsample validated and supplemented findings. Results Level I analysis yielded six key “determinants”—Institutional Relationships, Resource Availability, Data Strategy, Response to Change, Leadership Support, and Degree of Mission Alignment—which, according to local context, affect use of EHR data for research and QI. Level II analysis contextualized these determinants in a practical frame of reference, yielding a model of learning health system maturation, over-arching key concepts, and self-assessment questions to guide AHC progress toward becoming a learning health system. Level III informants validated and supplemented findings. Discussion Drawn from the collective knowledge of experienced informatics professionals, the findings and tools described offer practical support to help clinical informaticians leverage EHR data for research and QI in AHCs. Conclusion The learning health system model builds on the tripartite AHC mission of research, education, and patient care. AHCs must deliberately transform into learning health systems to capitalize fully on EHR data as a staple of health learning.","PeriodicalId":72041,"journal":{"name":"ACI open","volume":"04 1","pages":"e91 - e101"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1055/s-0040-1713421","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48353025","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"KOI Pond: The “Elevator Pitch” that Adapts to Describe the Breadth and Variety of Clinical Informatics Practice","authors":"J. Manning, Michael Wang, C. Sarabu, K. Goonan, W. Toth, Elijah J. Bell, J. F. Pearson, B. Levy","doi":"10.1055/s-0039-1701021","DOIUrl":"https://doi.org/10.1055/s-0039-1701021","url":null,"abstract":"Abstract Background The practice of clinical informatics (CI) is diverse and frequently tailored to individual skills and interests or to organizational/departmental needs. Prior studies have sought to define core content areas, educational milestones, and practice patterns within the clinical informatics subspecialty (CIS). Unfortunately, no single tool or framework currently exists that can succinctly define an informatician's role regardless of setting. The diversity of informatics practice makes it difficult to have one “pitch” that describes all possible domains, tasks, knowledge, and skills available to an informatician. Objective Using qualitative data from multiple informaticians, provide a succinct framework to describe and compartmentalize the various functions an informatician can contribute to the healthcare field. Methods We created an iterative focus group of five CIS fellows enrolled in different fellowship programs nationwide, one CIS program director, and an MD-PhD candidate in biomedical informatics. After much discussion, iteration, and consideration of career options within a young and burgeoning subspecialty, a dual-axis model was created that describes CIS practice in terms of settings (internal, external, and policy) and focus areas (knowledge, operations, and innovation). Results and Conclusion By combining both axes into a single “KOI pond” and then prioritizing sections by interest/resource investment, we are able to generate a unique snapshot for each informatician. These snapshots can be used (1) by informaticians to characterize their own practice succinctly as a pitch, (2) by CIS fellows who are considering career options, and (3) by those unfamiliar with CIS who want to learn more.","PeriodicalId":72041,"journal":{"name":"ACI open","volume":"04 1","pages":"e22 - e29"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1055/s-0039-1701021","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41568468","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Structuring Clinical Data for Improving Departmental Functionality","authors":"E. Levine","doi":"10.1055/s-0040-1709651","DOIUrl":"https://doi.org/10.1055/s-0040-1709651","url":null,"abstract":"Abstract A practical clinical information system used in a hospital's Department of Obstetrics and Gynecology is described, demonstrating its utility to automatically provide required regulatory reports and potential clinical performance improvement, in an easy-to-use way. Its use demonstrates how physician's workflow can be left unimpeded, while centralizing scribe activity to translate textually based documentation to structured data, to improve functionality within its departmental activity. The ability to easily view clinical trends from the collected data continues to demonstrate the value of structured data.","PeriodicalId":72041,"journal":{"name":"ACI open","volume":"04 1","pages":"e44 - e47"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1055/s-0040-1709651","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45213595","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effective Design, Development, and Evaluation of Video Tutorials for Electronic Medical Record Training","authors":"G. Randhawa, A. Shachak, K. Courtney, A. Kushniruk","doi":"10.1055/s-0040-1708036","DOIUrl":"https://doi.org/10.1055/s-0040-1708036","url":null,"abstract":"Abstract Background Electronic medical record (EMR) use by primary care physicians (PCP) in the United States and Canada is suboptimal, especially for supporting chronic diseases like diabetes. PCPs need postimplementation training to achieve value-adding EMR use. Video tutorials demonstrate how to accomplish tasks using software. However, there is a dearth of research on the use of video tutorials for EMR training. Objective The purpose of the study was to design, develop, and evaluate video tutorials for training PCPs in using EMR advanced features for diabetes care. This study addressed three research questions related to PCP's views of video tutorials as an EMR training method/approach, barriers, and facilitators to applying the EMR video tutorials to PCPs' practice, and how the design of EMR video tutorials can be improved. Methods The overall research study employed a QUAN (qual) mixed methods approach with an embedded design. This article focuses on the qualitative phase of the mixed methods study. A series of four theory-informed and evidence-based video tutorials for diabetes care was developed with a physician champion. Qualitative data were collected at four time points: 1 month before (O1), immediately before (O2), 3 months after (O3), and 6 months (O4) after the intervention. Semistructured interviews with participants were held at O3 and O4. Qualitative data were analyzed using thematic analysis. Results In total, 14 PCPs from the overall study participated in interviews (78%). The thematic analysis of the qualitative data revealed seven themes, which fall into two main categories: (1) design and development of EMR video tutorials, and (2) adoption and use of EMR video tutorials. Conclusion PCPs liked the EMR video tutorials for diabetes care, and would like more EMR video tutorials on various topics and EMR use levels. The study offers a roadmap for health informatics professionals everywhere to develop EMR training videos that meet evidence-based design criteria. It also help to identify opportunities to improve the design, delivery, and adoption of EMR video tutorials for future training interventions.","PeriodicalId":72041,"journal":{"name":"ACI open","volume":"04 1","pages":"e69 - e82"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1055/s-0040-1708036","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46465252","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Data-Driven Diabetes Education Guided by a Personalized Report for Patients on Insulin Pump Therapy.","authors":"Danielle Groat,&nbsp;Krystal Corrette,&nbsp;Adela Grando,&nbsp;Vaishak Vellore,&nbsp;Mike Bayuk,&nbsp;George Karway,&nbsp;Mary Boyle,&nbsp;Rozalina McCoy,&nbsp;Kevin Grimm,&nbsp;Bithika Thompson","doi":"10.1055/s-0039-1701022","DOIUrl":"https://doi.org/10.1055/s-0039-1701022","url":null,"abstract":"<p><strong>Objective: </strong>It is difficult to assess self-management behaviors (SMBs) and incorporate them into a personalized self-care plan. We aimed to develop and apply SMB phenotyping algorithms from data collected by diabetes devices and a mobile health (mHealth) application to create patient-specific SMBs reports to guide individualized interventions. Follow-up interventions aimed to understand patient's reasoning behind discovered SMB choices.</p><p><strong>Methods: </strong>This study deals with adults on continuous subcutaneous insulin infusion using a continuous glucose monitor (CGM) who self-tracked SMBs with an mHealth application for 1 month. Patient-generated data were quantified and an SMB report was designed and populated for each participant. A diabetes educator used the report to conduct personalized, data-driven educational interventions. Thematic analysis of the intervention was conducted.</p><p><strong>Results: </strong>Twenty-two participants recorded 118 alcohol, 251 exercise, 2,661 meal events, and 1,900 photos. A patient-specific SMB report was created from this data and used to conduct the educational intervention. High variability of SMB was observed between patients. There was variability in the percentage of alcohol events accompanied by a blood glucose check, median 79% (38-100% range), and frequency of changing the bolus waveform, median 11 (7-95 range). Interventions confirmed variability of SMBs. Main emerging themes from thematic analysis were: challenges and barriers, motivators, current SMB techniques, and future plans to improve glycemic control.</p><p><strong>Conclusion: </strong>The ability to quantify SMBs and understand patients' rationale may help improve diabetes self-care and related outcomes. This study describes our first steps in piloting a patient-specific diabetes educational intervention, as opposed to the current \"one size fits all\" approach.</p>","PeriodicalId":72041,"journal":{"name":"ACI open","volume":"4 1","pages":"e9-e21"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1055/s-0039-1701022","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39037632","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Establishing a Data-Sharing Environment for a 21st-Century Academic Health Center","authors":"Anjum Khurshid, Justin F. Rousseau, Steven B. Andrews, W. Tierney","doi":"10.1055/s-0040-1709652","DOIUrl":"https://doi.org/10.1055/s-0040-1709652","url":null,"abstract":"Abstract Objective The main purpose of this study was to establish a seamless clinical data sharing system in a new medical school in partnership with community health systems. Methods We developed a Data Request Management System (DRMS) and a data request process to streamline access to and management of data for quality improvement, population health, and research. We utilized a four-pronged methodology in implementing our clinical data sharing system: data governance, data extraction, external relationships, and internal engagement. Results The Data Core team of honest data brokers through the established relationships, data use agreements, data request processes, and the DRMS processed more than 50 data requests from all the departments during its first year of operation. The DRMS application and the supporting governance and relationships provided a platform for improved process and accuracy of data sharing environment by facilitating trust, transparency, standardization, and service provisioning. Conclusion Developing a seamless data ecosystem that forms the basis of a learning health system between an academic health center and community health systems requires a combination of people (the Data Core team), processes (common data request process policies and procedures), and technology (an effective online DRMS). Future work is needed to measure the impact of the clinical data sharing system on efficiency and accuracy of data sharing.","PeriodicalId":72041,"journal":{"name":"ACI open","volume":"04 1","pages":"e59 - e68"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1055/s-0040-1709652","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49526833","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Visualization of Electronic Health Record Data for Decision-Making in Diabetes and Congestive Heart Failure","authors":"S. Fischer, S. Fischer, S. Fischer, C. Safran, Krzysztof Z Gajos, A. Wright","doi":"10.1055/s-0040-1702213","DOIUrl":"https://doi.org/10.1055/s-0040-1702213","url":null,"abstract":"Abstract Objective The aim of this study is to study the impact of graphical representation of health record data on physician decision-making to inform the design of health information technology. Materials and Methods We conducted a within participants crossover design study using a simulated electronic health record (EHR) in which we presented cases with and without visualized data designed to highlight important clinical trends or relationships, followed by assessment of the impact on decision-making about next steps for patients with chronic diseases. We then asked whether trends were observed and about usability and satisfaction using validated usability questions and asked open-ended questions as well. Time to answer questions was also collected. Results Twenty-one primary care providers participated in the study, including five for testing only and sixteen for the full study. Questions about clinical assessment or next actions were answered correctly 55% of the time. Regarding objective trends in the data, participants described noticing the trends 85% of the time. Differences in noticing trends or difficulty level of questions were not statistically significant. Satisfaction with the tool was high and participants agreed strongly that it helped them make better decisions without adding to the time it took. Discussion The simulation allowed us to test the impact of a visualization on clinician practice in a realistic setting. Designers of EHRs should consider the ways information presentation can affect decision-making. Conclusion Testing visualization tools can be done in a clinically realistic context. Providers desire visualizations and believe that they help them make better and faster decisions.","PeriodicalId":72041,"journal":{"name":"ACI open","volume":"04 1","pages":"e35 - e43"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1055/s-0040-1702213","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42705824","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}